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Shirt Without Stripes

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Re: Shirt Without Stripes

#371

Post by tgv »

krick wrote: post #339
DenisM wrote: post #197

This problem is known as "attribution" - you have a "no" or "without" in the sentence, but you don't know where it belongs. One could (and one does) argue that the problem cannot be solved with statistical methods (ML), especially not in any domain where accuracy is required, such as medical recored analysis: "no evidence of cancer" and "evidence of no cancer" are very different things. Zooming out, the language fiel…

This is pointless overcomplicating. I might agree if the example would be slightly more interesting, but "without stripes" isn't even "absence of ", it is essentially a colour/pattern and can be easily attributed to a range of things exactly the same way "green" can be. Google translate correctly associates much more dubious and abstract concepts than that, and does it with statistical methods, i.e. associating word…

Google translate doesn't understand what it translates either. It just relies on a very large corpus of parallel texts.

Re: Shirt Without Stripes

#373

Post by hammock »

DenisM wrote: post #370
albertzeyer wrote: post #243

Why should it not be possible to solve this with statistical methods? The model just needs to be able to understand the important meaning of "no" in here, in the context of the whole sentence. I would guess that most modern NNs from the NLP area (Transformer or LSTM) would be able to correctly differentiate the meaning. The problem is, I think there is no fancy NN (yet) behind Google search, and the other web searche…

This very question was the subject of a lengthy debate between Norvig and Chomsky. I won't rehash it here, but here's a glimpse: Chomsky: Statistical analysis of snowflakes falling outside the window may predict the next snowflake, but it will do very little for weather prediction, and nothing for climate analysis. Norvig: Give us enough data and we will get close enough for all practical purposes.

This kind of reminds me of the plot of the current season on Westworld (no spoilers). The amount of data needed to really have "enough data" is often not practical, therefore (ironically) never letting you apply it "for practical purposes."

Re: Shirt Without Stripes

#374

Post by hammock »

rhizome wrote: post #356
albertzeyer wrote: post #243

Why should it not be possible to solve this with statistical methods? The model just needs to be able to understand the important meaning of "no" in here, in the context of the whole sentence. I would guess that most modern NNs from the NLP area (Transformer or LSTM) would be able to correctly differentiate the meaning. The problem is, I think there is no fancy NN (yet) behind Google search, and the other web searche…

> The model just needs to be able to understand the important meaning of "no" in here, in the context of the whole sentence It's easy to say, isn't it? Unfortunately, sticking the word "just" in there doesn't affect the difficulty. I do it all the time, too. That said, "meaning" is not statistical.

Why is it hard? Honestly. Add a "t" to "no" and you get a basic Boolean query.

Re: Shirt Without Stripes

#375

Post by 205guy »

Alex3917 wrote: post #212
rgovostes wrote: post #23

The point that the author is making, in a very understated way, is that all three companies have PR websites that breathlessly describe their advanced AI capabilities, yet they cannot understand a very simple query that young children can.

At least this is relatively innocuous. Until recently if you did a Google Image Search for "person" or "people", it only showed white men.

And when I search for "men without hats" I see men from Men Without Hats with hats. Language is hard.

Re: Shirt Without Stripes

#376

Post by skywhopper »

ipsum2 wrote: post #333
floatingatoll wrote: post #273

Earlier quoted context omitted.

Google was good at launch because it was harvesting data from webrings and directories to provide it "high quality" link ranking data. However, they didn't thank or credit or share any of their revenue with the sites whose human curation helped their results become so impressive. Seeing that Google search was effective, most human curators stopped curating directories and webrings. The SEO industry picked up the slac…

I disagree with your first point but agree with your second. Google obsoleted most webrings/directories because page rank was a better way of calculating a websites popularity. Then, websites figured out how to game page rank, and its been a gradual decline ever since.

The point is that the web rings and directories were an important source of good PageRank input. By killing them off, Google basically clearcut all their resources and did nothing to replant, and now the web is becoming a desert where nothing can grow.

Re: Shirt Without Stripes

#377

Post by ddebernardy »

PeterCorless wrote: post #117
ddebernardy wrote: post #112

The correct query would have been "shirt -stripes". That works fine, or at least does on Google. But yeah, sentence parsing fail.

Literally the first image that comes up for me is a striped shirt.

No idea where you're from or what you did...

https://imgur.com/a/XBzfOsF

Might your search history be so that you're so contrarian that Google suggests contrarian results? :D

Re: Shirt Without Stripes

#379

Post by [deleted] »

chrisseaton wrote: post #201
exhilaration wrote: post #181

Earlier quoted context omitted.

I disagree, "shirt without stripes" is an unusual word choice, not one that our ML models would be optimized for. Try "solid color shirt" and you'll see how much better the results are - at least on Google.

> "shirt without stripes" is an unusual word choice Lol what? These are words a toddler would understand.

[deleted]

Re: Shirt Without Stripes

#380

Post by disqard »

lolc wrote: post #279
pugworthy wrote: post #254

Interestingly, Google can handle these searches just fine... "birds without flight" "cars without wheels" "cats without tails" "dogs without hair" "intersections without lights" "poems without rhyme" "shirts without collars" (also "sleeves", "shoulders", "buttons", "logos", "pockets", and more)

That's because all these things are readily labelled by humans as such. So they don't have to understand the sentence. Just match it.

There's a larger, nuanced point here: statistical ML based "AI" is simply an API over aggregated samples of human intelligence. The sampling suffers from bias (the "white men" example in this thread), gaps (the OP's example, which relies on "shirts without stripes" being an uncommon, though perfectly acceptable phrase), and many more such shortcomings of what is essentially "rote learning".
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